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Identification of sex depending on radiological examination of foot and patella
Authors:Abdel Moneim Wafaa M  Abdel Hady Randa H  Abdel Maaboud Ragaa M  Fathy Hala M  Hamed Ahmed Mostafa
Affiliation:Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Assiut University, Assiut, Egypt.
Abstract:Forensic anthropology involves the building of an antemortem profile of an individual from skeletal remains. This includes sex, race determination, and age and stature estimation. Because most bones that are conventionally used for sex determination are often recovered either in a fragmented or incomplete state, it has become necessary to use denser bones that are often recovered intact, eg, the patella, calcaneus, and talus. The present work was performed to investigate the possibility of estimation of sex from some radiologic measurements among a known cross-section of Egyptian population. In this study lateral and anteroposterior radiographs of the right foot and knee were made on 160 living unfractured and nonpathologic individuals comprising 80 males and 80 females aged 25 to 65 years referred to the Radiology Department of Assiut University Hospital. Two measurements on right patella (maximum height and maximum width) and 2 measurements of metatarsal bones (length and midshaft diameter), were used to determine sex by univariate and multivariate discriminant analysis. Eighty radiographs of foot and patella of individuals not used in the original sample were randomly selected to test the accuracy of this method. The study revealed that significant sex differences were demonstrated based on these measurements taken on metatarsal bones more than on patella. One function associating 2 parameters (length and midshaft) of the third metatarsal bone obtained the highest value of correct sex determination with rate of 100% accuracy. The multivariate function associating length of the first, third, and fifth metatarsal bones and midshaft of first, second, and fifth metatarsal gave 100% accuracy. Test of multivariate function on the independent sample revealed a correct classification of 87.5%.
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